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131031s2014 gw | s |||| 0|eng d |
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|a 9783319012858
|9 978-3-319-01285-8
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|a 10.1007/978-3-319-01285-8
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|a 006.3
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|a Computational Models of Complex Systems
|h [electronic resource] /
|c edited by Vijay Kumar Mago, Vahid Dabbaghian.
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2014.
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| 300 |
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|a X, 196 p. 85 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Intelligent Systems Reference Library,
|x 1868-4394 ;
|v 53
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| 505 |
0 |
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|a Computational Models of Complex Systems: An Introduction -- Kabbalah Mathematical System Theoretic Models of Knowledge Based and Behavioral Economics and Finance -- The Commodity Exporting Country: A Spectral Analysis of Brazilian and Australian Financial Markets -- Probabilistic European country risk score forecasting using an epidemiological mathematical model -- Determining the ‘fault zone’ of fall events in Long Term Care -- Artificial Neural Network Based Approach for Classification of Child Disability -- Evaluating video and facial muscle activity for a better assistive technology: a silent speech-based HCl -- Modelling Replace/Repair Criteria for Returned Biomedical Devices in a Lean Manufacturing Environment -- A complex system approach for spatial modeling of land-use change and settlement growth in early agricultural societies -- City System Vulnerability and Resilience: Oscillatory Dynamics of Urban Hierarchies -- Introducing the Terrorism and Extremism Network Extractor -- Sampling Emerging Threats in Facebook using Bio-inspired Strategies (Random Walks).
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|a Computational and mathematical models provide us with the opportunities to investigate the complexities of real world problems. They allow us to apply our best analytical methods to define problems in a clearly mathematical manner and exhaustively test our solutions before committing expensive resources. This is made possible by assuming parameter(s) in a bounded environment, allowing for controllable experimentation, not always possible in live scenarios. For example, simulation of computational models allows the testing of theories in a manner that is both fundamentally deductive and experimental in nature. The main ingredients for such research ideas come from multiple disciplines and the importance of interdisciplinary research is well recognized by the scientific community. This book provides a window to the novel endeavours of the research communities to present their works by highlighting the value of computational modelling as a research tool when investigating complex systems. We hope that the readers will have stimulating experiences to pursue research in these directions.
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| 650 |
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0 |
|a Engineering.
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| 650 |
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0 |
|a Artificial intelligence.
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| 650 |
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0 |
|a Computational intelligence.
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| 650 |
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0 |
|a Complexity, Computational.
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| 650 |
1 |
4 |
|a Engineering.
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| 650 |
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4 |
|a Computational Intelligence.
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| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
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| 650 |
2 |
4 |
|a Complexity.
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| 700 |
1 |
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|a Mago, Vijay Kumar.
|e editor.
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| 700 |
1 |
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|a Dabbaghian, Vahid.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783319012841
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| 830 |
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|a Intelligent Systems Reference Library,
|x 1868-4394 ;
|v 53
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-319-01285-8
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-ENG
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| 950 |
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|a Engineering (Springer-11647)
|
